Allelic Diversity Changes in 96 Canadian Oat Cultivars Released from 1886 to 200<sup>1</sup>
Bibliographic record
Abstract
There is longstanding concern that modern plant breeding reduces crop genetic diversity. Such reduction may have consequences both for the vulnerability of crops to changes in their pests and diseases and for their ability to respond to changes in climate and agricultural practices. This concern, however, has not been well validated in recent molecular studies of genetic diversity of several crop species. The objective of this study was to assess allelic diversity changes in 96 Canadian oat (Avena sativa L.) cultivars released from 1886 to 2001 by means of 30 simple sequence repeats (SSRs). A total of 62 alleles were found from 11 informative SSR loci. Thirty‐nine alleles were detected infrequently (frequency ≤ 0.15) among the cultivars and only two alleles were observed frequently (frequency ≥ 0.95). Analyses of the dynamics of SSR alleles over time in these oat cultivars revealed random patterns of allelic change at three loci, shifting patterns of change at one locus, increasing patterns of change at two loci, and decreasing patterns of change at five loci. Significant decrease of alleles was detected in cultivars released after 1970 and also in some specific breeding programs. Three different band‐sharing analyses of the genetic diversity of the grouped cultivars, however, failed to detect significant diversity changes among cultivars released from different breeding periods or programs. These findings indicate that allelic diversity at particular loci, rather than average genetic diversity, is sensitive to oat breeding practices. They also indicate the need for attention to be paid to oat germplasm conservation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".